Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios
Southwest coastal Bangladesh, situated within the Ganges-Brahmaputra-Meghna delta, is one of the world’s most climate-vulnerable areas, confronting elevated sea levels, saline intrusion, tidal inundation, and cyclonic storms that threaten crops and livelihoods. Understanding long-term climatic patte...
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Institute of Remote Sensing and GIS
2025
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| author | Haque, Nasirul Noor, Salma Mondal, Krishna Prosad Shahriar, Shihab Ahmed Rahman, Shahriar Md. Arifur Tuli, Rajsree Das |
| author_facet | Haque, Nasirul Noor, Salma Mondal, Krishna Prosad Shahriar, Shihab Ahmed Rahman, Shahriar Md. Arifur Tuli, Rajsree Das |
| author_sort | Haque, Nasirul |
| collection | OJS |
| description | Southwest coastal Bangladesh, situated within the Ganges-Brahmaputra-Meghna delta, is one of the world’s most climate-vulnerable areas, confronting elevated sea levels, saline intrusion, tidal inundation, and cyclonic storms that threaten crops and livelihoods. Understanding long-term climatic patterns in this area is essential for developing localized adaptation and management solutions. This study aims to examine historical and projected patterns in temperature and precipitation to evaluate probable future climatic conditions under global climate scenarios. Future climate projections for the Khulna Division in the southwest part of Bangladesh using a statistical downscaling approach based on multiple Representative Concentration Pathways (2.5, 4.5, and 8.5) and Special Report on Emission Scenarios (SRES A2 and A1B). A Statistical Downscaling Model (SDSM) was used to downscale two Global Circulation Models (GCMs) viz CanESM2 and CGCM3. The models were evaluated against observed minimum and maximum temperature and precipitation data for the 30-year period 1987-2017. In addition, the downscaled climate variables were subjected to bias correction. During model calibration using NCEP predictors, the explained variances for CanESM2 and CGCM3 were 92.3% and 78% for Tmax, 28.02% and 45.36% for Tmin, and 9.28% and 10.11% for precipitation. The average R2 values during validation ranged from 0.82 to 0.89 for Tmax, 0.61 to 0.88 for Tmin, and 0.32 to 0.47 for precipitation. These results indicate good applicability of SDSM for downscaling daily minimum and maximum temperature and precipitation under different scenarios for future periods in the 2020s, 2050s, and 2080s. For CanESM2, changes in minimum annual temperature are projected to increase by 0.45°C, 0.46°C, and 0.63°C by 2080 for RCP 2.6, RCP 4.5 and RCP 8.5 scenarios, respectively. CGCM3 projected a maximum temperature increase of 0.32°C and 0.31°C by 2080 under the SRES A2 and A1B scenarios, respectively. Precipitation is projected to increase 0.46mm, 0.71mm and 1.28mm for RCP 2.6, RCP 4.5 and RCP 8.5, respectively, by the end of this century and 0.77mm and 0.87mm under the A1B and A2 scenarios, respectively, for the same period. |
| format | Online |
| id | ojs-269 |
| institution | My University |
| language | eng |
| publishDate | 2025 |
| publisher | Institute of Remote Sensing and GIS |
| record_format | ojs |
| spelling | ojs-2692025-11-13T10:06:58Z Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios Haque, Nasirul Noor, Salma Mondal, Krishna Prosad Shahriar, Shihab Ahmed Rahman, Shahriar Md. Arifur Tuli, Rajsree Das Climate Model Regional Scale Downscaling SDSM GCM RCP Southwest coastal Bangladesh, situated within the Ganges-Brahmaputra-Meghna delta, is one of the world’s most climate-vulnerable areas, confronting elevated sea levels, saline intrusion, tidal inundation, and cyclonic storms that threaten crops and livelihoods. Understanding long-term climatic patterns in this area is essential for developing localized adaptation and management solutions. This study aims to examine historical and projected patterns in temperature and precipitation to evaluate probable future climatic conditions under global climate scenarios. Future climate projections for the Khulna Division in the southwest part of Bangladesh using a statistical downscaling approach based on multiple Representative Concentration Pathways (2.5, 4.5, and 8.5) and Special Report on Emission Scenarios (SRES A2 and A1B). A Statistical Downscaling Model (SDSM) was used to downscale two Global Circulation Models (GCMs) viz CanESM2 and CGCM3. The models were evaluated against observed minimum and maximum temperature and precipitation data for the 30-year period 1987-2017. In addition, the downscaled climate variables were subjected to bias correction. During model calibration using NCEP predictors, the explained variances for CanESM2 and CGCM3 were 92.3% and 78% for Tmax, 28.02% and 45.36% for Tmin, and 9.28% and 10.11% for precipitation. The average R2 values during validation ranged from 0.82 to 0.89 for Tmax, 0.61 to 0.88 for Tmin, and 0.32 to 0.47 for precipitation. These results indicate good applicability of SDSM for downscaling daily minimum and maximum temperature and precipitation under different scenarios for future periods in the 2020s, 2050s, and 2080s. For CanESM2, changes in minimum annual temperature are projected to increase by 0.45°C, 0.46°C, and 0.63°C by 2080 for RCP 2.6, RCP 4.5 and RCP 8.5 scenarios, respectively. CGCM3 projected a maximum temperature increase of 0.32°C and 0.31°C by 2080 under the SRES A2 and A1B scenarios, respectively. Precipitation is projected to increase 0.46mm, 0.71mm and 1.28mm for RCP 2.6, RCP 4.5 and RCP 8.5, respectively, by the end of this century and 0.77mm and 0.87mm under the A1B and A2 scenarios, respectively, for the same period. Institute of Remote Sensing and GIS 2025-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Conference Proceedings Submission application/pdf http://journals.juniv.edu/index.php/jgs/article/view/269 10.59185/jgs.v1i1.269 Jahangirnagar University Journal of Geospatial Sciences; Vol. 1 No. 1 (2025); 59-83 3104-3917 3104-3909 10.59185/jgs.v1i1 eng http://journals.juniv.edu/index.php/jgs/article/view/269/215 Copyright (c) 2025 Jahangirnagar University Journal of Geospatial Sciences |
| spellingShingle | Climate Model Regional Scale Downscaling SDSM GCM RCP Haque, Nasirul Noor, Salma Mondal, Krishna Prosad Shahriar, Shihab Ahmed Rahman, Shahriar Md. Arifur Tuli, Rajsree Das Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios |
| title | Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios |
| title_full | Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios |
| title_fullStr | Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios |
| title_full_unstemmed | Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios |
| title_short | Projecting Climate Trends of Southwest Coastal Bangladesh under Global Climate Scenarios |
| title_sort | projecting climate trends of southwest coastal bangladesh under global climate scenarios |
| topic | Climate Model Regional Scale Downscaling SDSM GCM RCP |
| topic_facet | Climate Model Regional Scale Downscaling SDSM GCM RCP |
| url | http://journals.juniv.edu/index.php/jgs/article/view/269 |
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